Electronic documents include various types of information, for example, grayscale or continuous tone (contone) images, halftone images of different frequencies, text/line art, etc., in different formats that is suitable for being displayed or printed. Each information type may be part of a scanned document or an original image that is often processed using any of wide variety of techniques based on their suitability in terms of processing efficiency and reproduction resolution.
The halftone images include a pattern of dots (or halftones) of varying sizes and density that create an illusion of contone images. Typically, the halftone images are divided into different classes based on their halftone frequency for accurate selection of a processing technique to reproduce scanned halftone images. For example, when the halftone frequency is, for example, below 130 cells per inch (cpi), a halftone portion is classified as a low frequency halftone. Similarly, the halftone images are also classified into middle and high frequency halftones based on predefined frequency ranges.
While simple processing techniques (e.g., halftone zone thresholding, etc.) work fine for low frequency halftone detection, the relatively higher frequency halftones typically require complex techniques (e.g., based on pattern training, image segmentation, gradient estimation, wavelet-based image decomposition, or maximum a posteriori (MAP) probability estimation, etc.) for being detected. In this regard, some of the techniques for higher halftone frequency detection are discussed in U.S. Pat. No. 6,185,335 (Feb. 6, 2001), U.S. Pat. No. 6,683,702 B1 (Jan. 27, 2004), U.S. Pat. No. 6,185,328 B1 (Feb. 6, 2001), U.S. Pat. No. 8,184,340 (May 22, 2012), U.S. Pat. No. 6,734,991 (May 11, 2004). These conventional techniques for halftone frequency detection are computationally complex and require hardware acceleration to meet divergent processing needs of different frequency halftones. In other words, multiple processors are required to implement these techniques that adversely impact the device package size, cost, and power requirements.
Therefore, there exists a need for a low-cost and computationally efficient alternative to the existing hardware assisted methods and systems for halftone frequency detection while preserving the image quality and sharpness.